Applied Ordinal Logistic Regression Using Stata

From Single-Level to Multilevel Modeling
Author: Xing Liu
Publisher: SAGE Publications
ISBN: 1483319768
Category: Social Science
Page: 552
View: 8226
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The first book to provide a unified framework for both single-level and multilevel modeling of ordinal categorical data, Applied Ordinal Logistic Regression Using Stata by Xing Liu helps readers learn how to conduct analyses, interpret the results from Stata output, and present those results in scholarly writing. Using step-by-step instructions, this non-technical, applied book leads students, applied researchers, and practitioners to a deeper understanding of statistical concepts by closely connecting the underlying theories of models with the application of real-world data using statistical software.

Interaction Effects in Linear and Generalized Linear Models

Examples and Applications Using Stata
Author: Robert L. Kaufman
Publisher: SAGE Publications
ISBN: 1506365396
Category: Social Science
Page: 608
View: 5255
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Offering a clear set of workable examples with data and explanations, Interaction Effects in Linear and Generalized Linear Models is a comprehensive and accessible text that provides a unified approach to interpreting interaction effects. The book develops the statistical basis for the general principles of interpretive tools and applies them to a variety of examples, introduces the ICALC Toolkit for Stata (downloadable from the Robert L. Kaufman’s website), and offers a series of start-to-finish application examples to show students how to interpret interaction effects for a variety of different techniques of analysis, beginning with OLS regression. The data sets and the Stata code to reproduce the results of the application examples are available online.

Ökonometrie für Dummies


Author: Roberto Pedace
Publisher: John Wiley & Sons
ISBN: 3527801529
Category: Business & Economics
Page: 388
View: 5428
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Theorien verstehen und Techniken anwenden Was haben die Gehälter von Spitzensportlern und der Mindestlohn gemeinsam? Richtig, man kann sie mit Ökonometrie erforschen. Im Buch steht, wie es geht. Und nicht nur dafür, sondern für viele weitere Gebiete lohnt es sich, der zunächst etwas trocken und sperrig anmutenden Materie eine Chance zu geben. Lernen Sie von den Autoren, wie Sie spannende Fragen formulieren, passende Variablen festlegen, treffsichere Modelle entwerfen und Ihre Aussagen auf Herz und Nieren prüfen. Werden Sie sicher im Umgang mit Hypothesentests, Regressionsmodellen, Logit- & Probit-Modellen und allen weiteren gängigen Methoden der Ökonometrie. So begleitet Ökonometrie für Dummies Sie Schritt für Schritt und mit vielen Beispielen samt R Output durch dieses spannende Thema.

Applied Statistics Using Stata

A Guide for the Social Sciences
Author: Mehmet Mehmetoglu,Tor Georg Jakobsen
Publisher: SAGE
ISBN: 1473987903
Category: Social Science
Page: 376
View: 6912
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Clear, intuitive and written with the social science student in mind, this book represents the ideal combination of statistical theory and practice. It focuses on questions that can be answered using statistics and addresses common themes and problems in a straightforward, easy-to-follow manner. The book carefully combines the conceptual aspects of statistics with detailed technical advice providing both the ‘why’ of statistics and the ‘how’. Built upon a variety of engaging examples from across the social sciences it provides a rich collection of statistical methods and models. Students are encouraged to see the impact of theory whilst simultaneously learning how to manipulate software to meet their needs. The book also provides: Original case studies and data sets Practical guidance on how to run and test models in Stata Downloadable Stata programmes created to work alongside chapters A wide range of detailed applications using Stata Step-by-step notes on writing the relevant code. This excellent text will give anyone doing statistical research in the social sciences the theoretical, technical and applied knowledge needed to succeed.

Logistic Regression Models


Author: Joseph M. Hilbe
Publisher: CRC Press
ISBN: 1420075772
Category: Mathematics
Page: 656
View: 6110
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Logistic Regression Models presents an overview of the full range of logistic models, including binary, proportional, ordered, partially ordered, and unordered categorical response regression procedures. Other topics discussed include panel, survey, skewed, penalized, and exact logistic models. The text illustrates how to apply the various models to health, environmental, physical, and social science data. Examples illustrate successful modeling The text first provides basic terminology and concepts, before explaining the foremost methods of estimation (maximum likelihood and IRLS) appropriate for logistic models. It then presents an in-depth discussion of related terminology and examines logistic regression model development and interpretation of the results. After focusing on the construction and interpretation of various interactions, the author evaluates assumptions and goodness-of-fit tests that can be used for model assessment. He also covers binomial logistic regression, varieties of overdispersion, and a number of extensions to the basic binary and binomial logistic model. Both real and simulated data are used to explain and test the concepts involved. The appendices give an overview of marginal effects and discrete change as well as a 30-page tutorial on using Stata commands related to the examples used in the text. Stata is used for most examples while R is provided at the end of the chapters to replicate examples in the text. Apply the models to your own data Data files for examples and questions used in the text as well as code for user-authored commands are provided on the book’s website, formatted in Stata, R, Excel, SAS, SPSS, and Limdep. See Professor Hilbe discuss the book.

Datenanalyse mit Stata

Allgemeine Konzepte der Datenanalyse und ihre praktische Anwendung
Author: Ulrich Kohler,Frauke Kreuter
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110469502
Category: Business & Economics
Page: 526
View: 7421
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Dieses Buch bietet eine Einführung in das Datenanalysepaket Stata und ist zugleich das einzige Buch über Stata, das auch Anfängern eine ausreichende Erklärung statistischer Verfahren liefert. „Datenanalyse mit Stata" ist kein Befehls-Handbuch sondern erläutert alle Schritte einer Datenanalyse an praktischen Beispielen. Die Beispiele beziehen sich auf Themen der öffentlichen Diskussion oder der direkten Umgebung der meisten Leser. Damit eignet sich diese Buch als Einstieg in Data Analytics in allen Disziplinen. Die neue Auflage bietet einen systematischeren Zugang zum Datenmanagement in Gegenwart von „Missing Values" und behandelt die in der Stata-Programmversion 14 implementierte Unicode-Codierung.

Zeitreihenmodelle


Author: Andrew C. Harvey
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3486786741
Category: Business & Economics
Page: 396
View: 5608
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Gegenstand des Werkes sind Analyse und Modellierung von Zeitreihen. Es wendet sich an Studierende und Praktiker aller Disziplinen, in denen Zeitreihenbeobachtungen wichtig sind.

Regression

Modelle, Methoden und Anwendungen
Author: Ludwig Fahrmeir,Thomas Kneib,Stefan Lang
Publisher: Springer-Verlag
ISBN: 3642018378
Category: Business & Economics
Page: 502
View: 5917
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In dem Band beschreiben die Autoren erstmals klassische Regressionsansätze und moderne nicht- und semiparametrische Methoden in einer integrierten und anwendungsorientierten Form. Um Lesern die Analyse eigener Fragestellungen zu ermöglichen, demonstrieren sie die praktische Anwendung der Konzepte und Methoden anhand ausführlicher Fallstudien. Geeignet für Studierende der Statistik sowie für Wissenschaftler und Praktiker, zum Beispiel in den Wirtschafts- und Sozialwissenschaften, der Bioinformatik und -statistik, Ökonometrie und Epidemiologie.

Logistic Regression

From Introductory to Advanced Concepts and Applications
Author: Scott Menard
Publisher: SAGE
ISBN: 1412974836
Category: Social Science
Page: 377
View: 3176
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Logistic Regression is designed for readers who have a background in statistics at least up to multiple linear regression, who want to analyze dichotomous, nominal, and ordinal dependent variables cross-sectionally and longitudinally.

Regression Models for Categorical Dependent Variables Using Stata, Second Edition


Author: J. Scott Long,Jeremy Freese
Publisher: Stata Press
ISBN: 1597180114
Category: Computers
Page: 527
View: 3787
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After reviewing the linear regression model and introducing maximum likelihood estimation, Long extends the binary logit and probit models, presents multinomial and conditioned logit models and describes models for sample selection bias.

Applied Logistic Regression


Author: David W. Hosmer, Jr.,Stanley Lemeshow,Rodney X. Sturdivant
Publisher: John Wiley & Sons
ISBN: 1118548353
Category: Mathematics
Page: 528
View: 5829
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A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.

SPSS 22

Einführung in die moderne Datenanalyse
Author: Achim Bühl
Publisher: N.A
ISBN: 9783868942491
Category: SPSS (Computer system)
Page: 1055
View: 7906
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Moderne Ökonometrie


Author: Marno Verbeek
Publisher: VCH
ISBN: 9783527507665
Category:
Page: 534
View: 1587
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"Moderne Ökonometrie" stellt eine Vielzahl moderner und alternativer Ökonometrie-Methoden dar. Im Vordergrund steht die Anwendung der ökonometrischen Verfahren, die mit zahlreichen Beispielen erklärt werden. Die theoretischen Ausführungen werden auf das Nötigste beschränkt.

Tagebuch über die Informationstheorie


Author: Alfréd Rényi
Publisher: Birkhauser
ISBN: 9783764310066
Category: Mathematics
Page: 173
View: 580
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Logistic Regression

A Self-Learning Text
Author: David G. Kleinbaum,Mitchel Klein
Publisher: Springer Science & Business Media
ISBN: 0387216472
Category: Medical
Page: 514
View: 9945
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This is the second edition of this text on logistic regression methods, ori- nally published in 1994. As in the first edition, each chapter contains a presentation of its topic in “lecture-book” format together with objectives, an outline, key formulae, practice exercises, and a test. The “lecture-book” has a sequence of illust- tions and formulae in the left column of each page and a script (i.e., text) in the right column. This format allows you to read the script in conjunction with the illustrations and formulae that highlight the main points, formulae, or examples being presented. This second edition has expanded the first edition by adding five new ch- ters and a new appendix. The five new chapters are Chapter 9. Polytomous Logistic Regression Chapter 10. Ordinal Logistic Regression Chapter 11. Logistic Regression for Correlated Data: GEE Chapter 12. GEE Examples Chapter 13. Other Approaches for Analysis of Correlated Data Chapters 9 and 10 extend logistic regression to response variables that have more than two categories. Chapters 11–13 extend logistic regression to gen- alized estimating equations (GEE) and other methods for analyzing cor- lated response data. The appendix is titled “Computer Programs for Logistic Regression” and p- vides descriptions and examples of computer programs for carrying out the variety of logistic regression procedures described in the main text. The so- ware packages considered are SAS Version 8.0, SPSS Version 10.0, and STATA Version 7.0.

Multilevel and Longitudinal Modeling Using Stata, Second Edition


Author: Sophia Rabe-Hesketh,Anders Skrondal
Publisher: Stata Press
ISBN: 1597180408
Category: Business & Economics
Page: 562
View: 3851
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This is a book about applied multilevel and longitudinal modeling. Other terms for multilevel models include hierarchical models, random-effects or random-coefficient models, mixed-effects models, or simply mixed models. Longitudinal data are also referred to as panel data, repeated measures, or cross-sectional time series. A popular type of multilevel model for longitudinal data is the growth-curve model. Our emphasis is on explaining the models and their assumptions, applying the methods to real data, and interpreting results.

SPSS 14

Einführung in die moderne Datenanalyse
Author: Achim Bühl
Publisher: N.A
ISBN: 9783827372031
Category:
Page: 862
View: 6018
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Applied Survey Data Analysis


Author: Steven G. Heeringa,Brady T. West,Patricia A. Berglund
Publisher: CRC Press
ISBN: 9781420080674
Category: Mathematics
Page: 487
View: 5197
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Taking a practical approach that draws on the authors’ extensive teaching, consulting, and research experiences, Applied Survey Data Analysis provides an intermediate-level statistical overview of the analysis of complex sample survey data. It emphasizes methods and worked examples using available software procedures while reinforcing the principles and theory that underlie those methods. After introducing a step-by-step process for approaching a survey analysis problem, the book presents the fundamental features of complex sample designs and shows how to integrate design characteristics into the statistical methods and software for survey estimation and inference. The authors then focus on the methods and models used in analyzing continuous, categorical, and count-dependent variables; event history; and missing data problems. Some of the techniques discussed include univariate descriptive and simple bivariate analyses, the linear regression model, generalized linear regression modeling methods, the Cox proportional hazards model, discrete time models, and the multiple imputation analysis method. The final chapter covers new developments in survey applications of advanced statistical techniques, including model-based analysis approaches. Designed for readers working in a wide array of disciplines who use survey data in their work, this book also provides a useful framework for integrating more in-depth studies of the theory and methods of survey data analysis. A guide to the applied statistical analysis and interpretation of survey data, it contains many examples and practical exercises based on major real-world survey data sets. Although the authors use Stata for most examples in the text, they offer SAS, SPSS, SUDAAN, R, WesVar, IVEware, and Mplus software code for replicating the examples on the book’s website: http://www.isr.umich.edu/src/smp/asda/